Bheeshma KS

Sales quota analysis

•Built Regression model for prediction of quarterly sales quota.

•Involved in building end to end solution in Azure Databricks

•Project based on HP compensation program , developed in-house analytics solution to save 8 million annually.

Customer segmentation

•Developed use case for customer segmentation in Azure Databricks . •Designed pipeline in Azure ML studio and analyzed the results .

•Conducted RFM analysis on customer data.

Resolution code predictor

•Designed tree-based model to determine resolution code of a product problem text using NLP.

•Sales data analysis performed using historical data.

Freight cost optimization

•Built ML Regression model for prediction of cost incurred for shipments.

•Performed extensive EDA, trained and tested with multiple variations of data transformations to achieve better predicting model.

Auto Prioritizing Incident tickets

• Devised and deployed an Incident management tool, which auto prioritizes the tickets based on the criterions and keywords using Machine learning and text classification.
• Defined Triggers to auto analyze the new incidents on constant time intervals. And send customized emails based on the reprioritized tickets.

IDOCS Analysis - Time Series forecasting

NON-PO Payments fraud detection

PDF data extraction system